Fuzzy MABAC
Method object
- class pyfdm.methods.f_mabac.fMABAC(normalization=<function minmax_normalization>, defuzzify=<function mean_defuzzification>)[source]
Bases:
object
- __call__(matrix, weights, types, *args, **kwargs)[source]
Calculates the alternatives preferences
- Parameters:
matrix (ndarray) – Decision matrix / alternatives data. Alternatives are in rows and Criteria are in columns.
weights (ndarray) – Vector of criteria weights in a crisp form
types (ndarray) – Types of criteria, 1 profit, -1 cost
- Returns:
Preference calculated for alternatives. Greater values are placed higher in ranking
- Return type:
ndarray
Fuzzy calculations
- pyfdm.methods.mabac.fuzzy.fuzzy(matrix, weights, types, normalization, defuzzify)[source]
Calculates the alternatives preferences based on Triangular Fuzzy Number extension
- Parameters:
matrix (ndarray) – Decision matrix / alternatives data. Alternatives are in rows and Criteria are in columns.
weights (ndarray) – Vector of criteria weights in a crisp form
types (ndarray) – Types of criteria, 1 profit, -1 cost
normalization (callable) – Function used to normalize the decision matrix
defuzzify (callable) – Function used to defuzzify the TFN into crisp value
- Returns:
Crisp preferences of alternatives
- Return type:
ndarray